Optimization

TRAINING GENERATIVE ADVERSARIAL NETWORKS VIA PRIMAL-DUAL SUBGRADIENT METHODS: A LAGRANGIAN PERSPECTIVE ON GAN ICLR 2018 Trust Your Model: Light Field Depth Estimation With Inline Occlusion Handling CVPR 2018 Unbiased Online Recurrent Optimization ICLR 2018 Understanding Short-Horizon Bias in Stochastic Meta-Optimization ICLR 2018 Variance-Reduced Stochastic Gradient Descent on Streaming Data NeurIPS 2018 Weighted SGD for ℓ_p Regression with Randomized Preconditioning JMLR 2018 Which Training Methods for GANs do actually Converge? ICML 2018 Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization IJCAI 2017 Accumulated Gradient Normalization ACML 2017 Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation CVPR 2017 ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization NeurIPS 2017 A Greedy Approach for Budgeted Maximum Inner Product Search NeurIPS 2017 An experimental analysis of Noise-Contrastive Estimation: the noise distribution matters EACL 2017 A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting CVPR 2017 Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NeurIPS 2017 Collaborative Deep Learning in Fixed Topology Networks NeurIPS 2017 Concept Equalization to Guide Correct Training of Neural Machine Translation IJCNLP 2017 Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks NeurIPS 2017 Convex Global 3D Registration With Lagrangian Duality CVPR 2017 Decoding with Finite-State Transducers on GPUs EACL 2017 Deeply Aggregated Alternating Minimization for Image Restoration CVPR 2017 DOPE: Distributed Optimization for Pairwise Energies CVPR 2017 DSAC - Differentiable RANSAC for Camera Localization CVPR 2017 Dynamic Data Selection for Neural Machine Translation EMNLP 2017 Efficient Private ERM for Smooth Objectives IJCAI 2017